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Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - TRABIT (Translational Brain Imaging Training Network)

Teaser

Summary

\"In recent decades, medical imaging techniques such as computed tomography (CT), ultrasound (US), and especially magnetic resonance imaging (MRI) have gained a central role in the clinical management of disorders of the brain. Since brain imaging often visualizes disease effects with much greater sensitivity than clinical observation, it holds great promise to help diagnose patients at the earliest stages of their disease, when treatment is most effective; and personalize their treatment by evaluating their response to a specific intervention.

A fundamental bottleneck in translating the wealth of information contained in medical images into optimized patient care is the lack of patient-specific computational tools to help analyze and quantify the torrent of acquired imaging data. The last two decades of medical image computing research have matured to allow robust and automatic assessment of carefully homogenized scientific studies of mostly healthy brain scans. Yet analyzing the \"\"wild\"\" type of neuroimaging data arising in the standard clinical treatment of brain disorders remains a hard and unsolved problem.

The overall goal of the TRABIT project is to enlarge the scope of quantitative brain image analysis from scientific group studies of the human brain into improved healthcare delivery in clinical applications, benefitting individual patients suffering from brain disease. Towards this end, TRABIT aims to significantly advance the current state of the art in the field of computational neuroimaging to achieve the following specific research objectives:

- RO1: To develop fundamentally new computational models to reliably analyze clinical brain scans in several major brain disease categories;

- RO2: To implement the developed methods in software tools that can be robustly applied across imaging sites;

- RO3: To test and validate the proposed methods and tools on large collections of (multi-site) clinical neuroimaging data;

- RO4: To share the accomplished methodological advances across the network and beyond;

- RO5: To facilitate true clinical adoption of the developed methods and tools by strongly engaging with the medical imaging industry.

In order to achieve these ambitious research objectives, there is a strong need for a new generation of young European researchers capable of seamlessly combining a deep understanding of computational neuroimaging; the clinical needs and constraints arising in the treatment of brain disorders; and the commercialization processes needed to bring new research developments into actual clinical practice. Towards this goal, we are training 15 early-stage researchers, each with an individual research plan centered around one of four major brain disease categories - Multiple Sclerosis (WP1), Fetal Brain Disorders (WP2), Brain Tumors (WP3), and Stroke/Neurovascular Disease (WP4) - and each supervised by an academic, a clinical, and an industrial mentor.\"

Work performed

The work performed since the beginning of the project can be summarized as follows:

1. After a broad international call attracting 401 applicants from 67 different countries, we carefully selected 15 excellent early-stage researchers to be trained by the consortium. Each of these early-stage researchers is enrolled in an individual PhD program co-supervised by an academic, a clinical, and an industrial mentor. The researchers follow an individual research plan centered around one of the four major brain disease categories we aim to tackle.

2. So far we have organized three week-long training events: two TRABIT training schools (attended by all TRABIT early-stage researchers as well as 24 external PhD students) and one internal TRABIT workshop (focused on the TRABIT students\' research work). These events took place in Munich, Copenhagen and Lausanne, and offered 8 scientific courses as well as 4 transferable skills courses in total. Dedicated attention was given to hands-on training in a commonly adopted rapid-prototyping software environment to facilitate testing, demonstrating the developed tools in hospital environments, and disseminating the obtained models and methods.

3. Many TRABIT early-stage researchers are developing open-source software; some are contributing to patents and/or commercial software products & services; while yet others are focused on enabling future research activities outside the action. So far 13 full-length, peer-reviewed scientific articles have been published by the TRABIT students; in total they have already presented 17 papers or abstracts at international conferences or workshops.

4. We maintain an active website (https://www.trabit.eu/) that features a blog reporting on important project-related events; an automatic twitter feed displaying the messages posted on the TRABIT twitter account (https://twitter.com/TRABIT_ITN); and a half-yearly newsletter. The website serves as a central dissemination platform for the network, and contains all the information concerning the consortium, its early-stage researchers, the project objectives, TRABIT training events, and our publications.

Final results

The methods and tools developed by the TRABIT consortium are expected to significantly advance the state of the art in clinical neuroimaging, enabling improved detection and progress monitoring in a wide array of brain disorders, and optimizing healthcare delivery specifically tailored towards the needs of individual patients. Our research and training program is further set to generate 15 high-skilled scientists trained to take advantage of computational, clinical, and commercial opportunities in a key sector in Europe.